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credit_score's Introduction

Project Charter Draft

Business background

  • The primary clients are consumer lending companies, banks developing new consumer products.
  • Loan acceptance increase, profit increase

Scope

  • we are building AI-powered scoring solution provider
  • delivery mode: web-based application (probably Microsfot Azure Web App Service #?)

Metrics

Plan

  • Phases (milestones), timeline, short description of what we'll do in each phase.

Architecture

  • Data

    • What data do we expect? Raw historical data in in xls/csv format from the customer data sources (e.g. on-prem files, SQL, on-prem Hadoop etc.)
    • Sampled data enough for modeling

  • What tools and data storage/analytics resources will be used in the solution e.g.,

    • Azure Data Storage
    • Python/TensorFlow for feature construction, aggregation and sampling
    • AzureML for modeling and web service operationalization

  • How will the score or operationalized web service(s) (RRS and/or BES) be consumed in the business workflow of the customer?

    • Azure Web App API
    • How will the customer use the model results to make decisions: Power BI connected to Azure Stream Analytics
    • Data movement pipeline in production

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